2023
Longitudinal Patterns in Testosterone Prescribing After US FDA Safety Communication in 2014
Sankar A, Everhart A, Jena A, Jeffery M, Ross J, Shah N, Karaca-Mandic P. Longitudinal Patterns in Testosterone Prescribing After US FDA Safety Communication in 2014. The Joint Commission Journal On Quality And Patient Safety 2023, 49: 458-466. PMID: 37380503, DOI: 10.1016/j.jcjq.2023.05.003.Peer-Reviewed Original ResearchConceptsCoronary artery diseaseFDA safety communicationPhysician characteristicsLabel prescribingCare physiciansTestosterone prescribingService administrative claims dataNon-primary care physiciansCertain physician characteristicsDrug Administration (FDA) safety communicationPrimary care physiciansAdministrative claims dataCase mix indexTestosterone therapyArtery diseaseTestosterone prescriptionsPrescribing levelsMean agePrescription trendsTeaching hospitalClaims dataPrescription levelsMedicare feePrescribingUS Food
2021
Effects of forced disruption in Medicaid managed care on children with asthma
Piwnica‐Worms K, Staiger B, Ross JS, Rosenthal MS, Ndumele CD. Effects of forced disruption in Medicaid managed care on children with asthma. Health Services Research 2021, 56: 668-676. PMID: 33624290, PMCID: PMC8313960, DOI: 10.1111/1475-6773.13643.Peer-Reviewed Original ResearchConceptsPrimary care providersPersistent asthmaCare plansOutpatient visitsCare utilizationCare administrative claims dataEmergency department utilizationHealth care utilizationAdministrative claims dataIndicators of asthmaProportion of childrenPatients outpatientHealth utilizationAdministrative claimsAsthmaCare providersClaims dataNumber of childrenConsistent associationMedicaidVisitsChildrenOutpatientsPercentage point decreaseEnrollment data
2020
Attribution of Adverse Events Following Coronary Stent Placement Identified Using Administrative Claims Data
Dhruva SS, Parzynski CS, Gamble GM, Curtis JP, Desai NR, Yeh RW, Masoudi FA, Kuntz R, Shaw RE, Marinac‐Dabic D, Sedrakyan A, Normand S, Krumholz HM, Ross JS. Attribution of Adverse Events Following Coronary Stent Placement Identified Using Administrative Claims Data. Journal Of The American Heart Association 2020, 9: e013606. PMID: 32063087, PMCID: PMC7070203, DOI: 10.1161/jaha.119.013606.Peer-Reviewed Original ResearchMeSH KeywordsAdministrative Claims, HealthcareAgedAged, 80 and overCoronary RestenosisCoronary ThrombosisDatabases, FactualDrug-Eluting StentsFemaleHumansMaleMedicareMyocardial InfarctionPercutaneous Coronary InterventionProduct Surveillance, PostmarketingRegistriesRetreatmentRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeUnited StatesConceptsIndex percutaneous coronary interventionPercutaneous coronary interventionSame coronary arteryDrug-eluting stentsNCDR CathPCI RegistrySubsequent percutaneous coronary interventionAcute myocardial infarctionCoronary arteryClaims dataCathPCI RegistryAdverse eventsIndex procedureMyocardial infarctionRepeat percutaneous coronary interventionReal-world registry dataTarget vessel revascularizationCoronary stent placementAdministrative claims dataLong-term safetyLongitudinal claims dataPotential safety eventsVessel revascularizationCoronary interventionDES placementStent thrombosis
2019
Claims-based cardiovascular outcome identification for clinical research: Results from 7 large randomized cardiovascular clinical trials
Brennan JM, Wruck L, Pencina MJ, Clare RM, Lopes RD, Alexander JH, O'Brien S, Krucoff M, Rao SV, Wang TY, Curtis LH, Newby LK, Granger CB, Patel M, Mahaffey K, Ross JS, Normand SL, Eloff BC, Caños DA, Lokhnygina YV, Roe MT, Califf RM, Marinac-Dabic D, Peterson ED. Claims-based cardiovascular outcome identification for clinical research: Results from 7 large randomized cardiovascular clinical trials. American Heart Journal 2019, 218: 110-122. PMID: 31726314, DOI: 10.1016/j.ahj.2019.09.002.Peer-Reviewed Original ResearchMeSH KeywordsAgedBiomedical ResearchCardiovascular DiseasesCoronary Artery BypassData AccuracyDatabases, FactualFee-for-Service PlansFemaleFollow-Up StudiesHumansInpatientsInsurance Claim ReviewKaplan-Meier EstimateMaleMedical Record LinkageMedicareMulticenter Studies as TopicMyocardial InfarctionMyocardial RevascularizationRandomized Controlled Trials as TopicRetrospective StudiesStrokeUnited StatesConceptsCardiovascular clinical trialsMyocardial infarctionEvent ratesClinical researchRandomized cardiovascular clinical trialsClinical trialsTrial participantsClinical events committee’s adjudicationsOverall cardiovascular event ratesTreatment effectsAnnual event rateCardiovascular event ratesMedicare inpatient claimsClinical trial dataOutcomes of interestSite-reported eventsCase concordanceCardiovascular outcomesRetrospective studyHigher event ratesInpatient claimsClinical dataMedicare claimsClaims dataDuke DatabaseRates of Physician Coprescribing of Opioids and Benzodiazepines After the Release of the Centers for Disease Control and Prevention Guidelines in 2016
Jeffery MM, Hooten WM, Jena AB, Ross JS, Shah ND, Karaca-Mandic P. Rates of Physician Coprescribing of Opioids and Benzodiazepines After the Release of the Centers for Disease Control and Prevention Guidelines in 2016. JAMA Network Open 2019, 2: e198325. PMID: 31373650, PMCID: PMC6681551, DOI: 10.1001/jamanetworkopen.2019.8325.Peer-Reviewed Original ResearchConceptsLong-term opioid useOpioid usePrevention guidelinesMA groupDisease controlCoprescription of opioidsRetrospective cohort studyUS national databaseInsurance groupsMedicare AdvantageSickle cell diseaseGuideline releasePrescription daysPrescribed opioidsBenzodiazepine prescriptionsCohort studyMedian agePharmacy claimsChronic painCell diseaseCoprescriptionMAIN OUTCOMESame clinicianClaims dataHospice care
2017
Trends in readmission rates for safety net hospitals and non-safety net hospitals in the era of the US Hospital Readmission Reduction Program: a retrospective time series analysis using Medicare administrative claims data from 2008 to 2015
Salerno AM, Horwitz LI, Kwon JY, Herrin J, Grady JN, Lin Z, Ross JS, Bernheim SM. Trends in readmission rates for safety net hospitals and non-safety net hospitals in the era of the US Hospital Readmission Reduction Program: a retrospective time series analysis using Medicare administrative claims data from 2008 to 2015. BMJ Open 2017, 7: e016149. PMID: 28710221, PMCID: PMC5541519, DOI: 10.1136/bmjopen-2017-016149.Peer-Reviewed Original ResearchConceptsHospital Readmissions Reduction ProgramNon-safety net hospitalsSafety-net hospitalMedicare administrative claims dataReadmission ratesAdministrative claims dataNet hospitalReadmissions Reduction ProgramRetrospective time series analysisSafety netClaims dataTime series analysisSocioeconomic statusUnplanned readmission ratePrincipal discharge diagnosisLow socioeconomic statusInterrupted time seriesReduction programsFive-digit zip codeSeries analysisHRRP penaltiesIndex admissionHospital proportionDischarge diagnosisService patients
2016
Trends of Anti-Vascular Endothelial Growth Factor Use in Ophthalmology Among Privately Insured and Medicare Advantage Patients
Parikh R, Ross JS, Sangaralingham LR, Adelman RA, Shah ND, Barkmeier AJ. Trends of Anti-Vascular Endothelial Growth Factor Use in Ophthalmology Among Privately Insured and Medicare Advantage Patients. Ophthalmology 2016, 124: 352-358. PMID: 27890437, DOI: 10.1016/j.ophtha.2016.10.036.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAngiogenesis InhibitorsBevacizumabCohort StudiesDatabases, FactualDiabetic RetinopathyDrug UtilizationFemaleHumansInsurance, HealthIntravitreal InjectionsMacular DegenerationMaleMedicare Part CMiddle AgedOphthalmologyPrivate SectorRanibizumabReceptors, Vascular Endothelial Growth FactorRecombinant Fusion ProteinsRetinal Vein OcclusionRetrospective StudiesUnited StatesVascular Endothelial Growth Factor AYoung AdultConceptsAge-related macular degenerationDiabetic retinal diseaseAnti-VEGF injectionsIntravitreal anti-VEGF injectionsRetinal vein occlusionAdministrative claims dataRetinal diseasesOphthalmic diseasesVein occlusionClaims dataUse of bevacizumabCurrent Procedural Terminology codesPatients 18 yearsRetrospective cohort studyMedicare Advantage patientsOptumLabs Data WarehouseDrug Administration approvalProcedural Terminology codesGrowth factor useRanibizumab useBevacizumab useAvailable medicationsCohort studyMedication useCommon medicationsTrends in Drug Utilization, Glycemic Control, and Rates of Severe Hypoglycemia, 2006–2013
Lipska KJ, Yao X, Herrin J, McCoy RG, Ross JS, Steinman MA, Inzucchi SE, Gill TM, Krumholz HM, Shah ND. Trends in Drug Utilization, Glycemic Control, and Rates of Severe Hypoglycemia, 2006–2013. Diabetes Care 2016, 40: 468-475. PMID: 27659408, PMCID: PMC5360291, DOI: 10.2337/dc16-0985.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedBlood GlucoseComorbidityDiabetes Mellitus, Type 2Dipeptidyl-Peptidase IV InhibitorsDrug UtilizationFemaleGlycated HemoglobinHumansHypoglycemiaHypoglycemic AgentsInsulinLogistic ModelsMaleMetforminMiddle AgedRetrospective StudiesSulfonylurea CompoundsThiazolidinedionesYoung AdultConceptsGlycemic controlSevere hypoglycemiaOlder patientsDipeptidyl peptidase-4 inhibitorsGlucose-lowering drugsGlucose-lowering medicationsProportion of patientsOverall glycemic controlPeptidase-4 inhibitorsMedicare Advantage patientsSex-standardized ratesType 2 diabetesOverall rateClass of agentsMore comorbiditiesChronic comorbiditiesYounger patientsAdvantage patientsDrug utilizationClaims dataPatientsHypoglycemiaHemoglobin AT2DMComorbiditiesAdoption of new agents and changes in treatment patterns for hepatitis C: 2010-2014.
Yao X, Sangaralingham LR, Ross JS, Shah ND, Talwalkar JA. Adoption of new agents and changes in treatment patterns for hepatitis C: 2010-2014. The American Journal Of Managed Care 2016, 22: e224-32. PMID: 27355910.Peer-Reviewed Original ResearchMeSH KeywordsAdultAntiviral AgentsDatabases, FactualDrug Therapy, CombinationFemaleHealth Care CostsHepacivirusHepatitis C, ChronicHumansInsurance Claim ReviewInterferonsLogistic ModelsMaleMiddle AgedOligopeptidesPredictive Value of TestsRetrospective StudiesRibavirinSofosbuvirTreatment OutcomeUnited StatesConceptsTreatment ratesNew medicationsRetrospective analysisHepatitis C virus medicationsOptum Labs Data WarehouseUS commercial insurance databaseLedipasvir/sofosbuvirMedian OOP costsNew HCV medicationsInterferon/ribavirinInterferon-based regimensCommercial insurance databaseAdministrative claims dataChronic HCVLiver transplantElderly patientsHCV medicationsHepatitis CNew regimensLiver diseaseTreatment patternsInsurance databaseUrgent treatmentPrimary treatmentClaims dataLong-Term Risk for Device-Related Complications and Reoperations After Implantable Cardioverter-Defibrillator Implantation: An Observational Cohort Study.
Ranasinghe I, Parzynski CS, Freeman JV, Dreyer RP, Ross JS, Akar JG, Krumholz HM, Curtis JP. Long-Term Risk for Device-Related Complications and Reoperations After Implantable Cardioverter-Defibrillator Implantation: An Observational Cohort Study. Annals Of Internal Medicine 2016, 165: 20-29. PMID: 27135392, DOI: 10.7326/m15-2732.Peer-Reviewed Original ResearchICD-related complicationsNational Cardiovascular Data RegistryObservational cohort studyDevice-related complicationsICD implantationLong-term riskCohort studyMedicare feeNational Cardiovascular Data Registry ICD RegistryImplantable cardioverter defibrillator implantationImplantable cardioverter-defibrillator placementCardioverter-defibrillator implantationService claims dataCRT-D devicesSingle-chamber devicesCumulative incidenceNonfatal outcomesICD RegistryService patientsBlack raceFemale sexReoperationAmerican CollegeClaims dataComplications
2015
Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data
Horwitz LI, Grady JN, Cohen DB, Lin Z, Volpe M, Ngo CK, Masica AL, Long T, Wang J, Keenan M, Montague J, Suter LG, Ross JS, Drye EE, Krumholz HM, Bernheim SM. Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data. Journal Of Hospital Medicine 2015, 10: 670-677. PMID: 26149225, PMCID: PMC5459369, DOI: 10.1002/jhm.2416.Peer-Reviewed Original ResearchConceptsSame-hospital readmissionsNegative predictive valuePositive predictive valuePredictive valueReadmission measuresHospital-wide readmission measureGold standard chart reviewAdministrative claims-based algorithmDiagnostic cardiac catheterizationClaims-based algorithmLarge teaching centersAcute care hospitalsSmall community hospitalUnplanned readmissionChart reviewCardiac catheterizationScheduled careSpecificity 96.5Community hospitalReadmissionClaims dataCardiac devicesHealth systemTeaching centerPublic reporting
2014
Development and use of an administrative claims measure for profiling hospital-wide performance on 30-day unplanned readmission.
Horwitz LI, Partovian C, Lin Z, Grady JN, Herrin J, Conover M, Montague J, Dillaway C, Bartczak K, Suter LG, Ross JS, Bernheim SM, Krumholz HM, Drye EE. Development and use of an administrative claims measure for profiling hospital-wide performance on 30-day unplanned readmission. Annals Of Internal Medicine 2014, 161: s66-75. PMID: 25402406, PMCID: PMC4235629, DOI: 10.7326/m13-3000.Peer-Reviewed Original ResearchConceptsUnplanned readmissionReadmission measuresReadmission ratesReadmission riskMedicare feeHospital-wide readmission measureRisk-standardized readmission ratesPayer dataAdministrative Claims MeasureRisk-standardized ratesAverage-risk patientsUnplanned readmission rateDays of dischargeHospital risk-standardized readmission ratesAdult hospitalizationsComorbid conditionsPrincipal diagnosisClaims dataService claimsService beneficiariesReadmissionMeasure development studiesMedicaid ServicesRisk adjustmentHospital
2013
Regional Density of Cardiologists and Rates of Mortality for Acute Myocardial Infarction and Heart Failure
Kulkarni VT, Ross JS, Wang Y, Nallamothu BK, Spertus JA, Normand SL, Masoudi FA, Krumholz HM. Regional Density of Cardiologists and Rates of Mortality for Acute Myocardial Infarction and Heart Failure. Circulation Cardiovascular Quality And Outcomes 2013, 6: 352-359. PMID: 23680965, PMCID: PMC5323047, DOI: 10.1161/circoutcomes.113.000214.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overCardiologyCohort StudiesFemaleHealth Services AccessibilityHealth Services Needs and DemandHealthcare DisparitiesHeart FailureHospitalizationHumansLinear ModelsLogistic ModelsMaleMedicareMyocardial InfarctionOdds RatioPhysiciansPneumoniaPrognosisResidence CharacteristicsRisk AssessmentRisk FactorsTime FactorsUnited StatesWorkforceConceptsAcute myocardial infarctionHeart failureHospital referral regionsMortality riskLowest quintileMyocardial infarctionReferral regionsMedicare administrative claims dataCharacteristics of patientsRisk of deathAdministrative claims dataHierarchical logistic regression modelsLogistic regression modelsRate of mortalityRegional densityHighest quintileNumber of cardiologistsWorse outcomesClaims dataPatientsPneumoniaCardiologistsHospitalizationAdmissionQuintile
2012
Skilled Nursing Facility Referral and Hospital Readmission Rates after Heart Failure or Myocardial Infarction
Chen J, Ross JS, Carlson MD, Lin Z, Normand SL, Bernheim SM, Drye EE, Ling SM, Han LF, Rapp MT, Krumholz HM. Skilled Nursing Facility Referral and Hospital Readmission Rates after Heart Failure or Myocardial Infarction. The American Journal Of Medicine 2012, 125: 100.e1-100.e9. PMID: 22195535, PMCID: PMC3246370, DOI: 10.1016/j.amjmed.2011.06.011.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionRisk-standardized readmission ratesSkilled nursing facilitiesHeart failureHospital-level variationReadmission ratesMyocardial infarctionRate of dischargeHospital-level readmission ratesSubstantial hospital-level variationService Medicare patientsCause readmission rateRisk of readmissionHospital readmission ratesHF admissionsRegression modelsAMI patientsFacility referralPrincipal diagnosisMedicare patientsMedicare claimsClaims dataAMI admissionsAMI hospitalizationNursing facilities